D o m e n ic o B ia n c u lli

Cyber-physical systems (CPSs) typically consist of a wide set of integrated, heterogeneous components; consequently, most of their critical failures relate to the interoperability of such components. Unfortunately, most CPS test automation techniques are preliminary and industry still heavily relies on manual testing. With potentially incomplete, manually-generated test suites, it is of paramount importance to assess their quality. Though mutation analysis has demonstrated to be an effective means to assess test suite quality in some specific contexts, we lack approaches for CPSs. Indeed, existing approaches do not target interoperability problems and cannot be executed in the presence of black-box or simulated components, a typical situation with CPSs. In this paper, we introduce data-driven mutation analysis, an approach that consists in assessing test suite quality by verifying if it detects interoperability faults simulated by mutating the data exchanged by software components. To this end, we describe a data-driven mutation analysis technique (DaMAT ) that automatically alters the data exchanged through data buffers. Our technique is driven by fault models in tabular form where engineers specify how to mutate data items by selecting and configuring a set of mutation operators. We have evaluated DaMAT with CPSs in the space domain; specifically, the test suites for the software systems of a microsatellite and nanosatellites launched on orbit last year. Our results show that the approach effectively detects test suite shortcomings, is not affected by equivalent and redundant mutants, and entails acceptable costs.

ThEodorE is a trace checker for Cyber-Physical systems (CPS). It provides users with (i) a GUI editor for writing CPS requirements; (ii) an automatic procedure to check whether the requirements hold on execution traces of a CPS. ThEodorE enables writing requirements using the Hybrid Logic of Signals (HLS), a novel, logic-based specification language to express CPS requirements. The trace checking procedure of ThEodorE reduces the problem of checking if a requirement holds on an execution trace to a satisfiability problem, which can be solved using off-the-shelf Satisfiability Modulo Theories (SMT) solvers. This artifact paper presents the tool support provided by ThEodorE.

We present DaMAT, a tool that implements datadriven mutation analysis. In contrast to traditional code-driven mutation analysis tools it mutates (i.e., modifies) the data exchanged by components instead of the source of the software under test. Such an approach helps ensure that test suites appropriately exercise components interoperability -essential for safety-critical cyber-physical systems. A user-provided fault model drives the mutation process. We have successfully evaluated DaMAT on software controlling a microsatellite and a set of libraries used in deployed CubeSats. A demo video of DaMAT is available at https://youtu.be/s5M52xWCj84

Ardeidae tend to exhibit low sexual dimorphism, both in size and plumage coloration, making sex attribution in the field challenging for both birdwatchers and ringers. Here, we assessed whether biometrics and plumage patterns are a good proxy for sex assignment in the Purple Heron (Ardea purpurea). We based our work on 27 molecularly-sexed free-living adults captured in Italy and Romania during the breeding season from 2018 to 2021. We found significant sexual size dimorphism in the beak, which resulted longer in males, but not in weight, wing, tarsus or sternum length. Birds with darker plumages, stronger contrast between reddish ornamental feathers and blackish mantle were classified as males, allowing for correct sex attribution in 70% of the males and 73 % of the females. On the one hand, we concluded that molecular sexing is the most reliable approach for sex attribution in this species. On the other hand, we also found that trained ringers or expert observers may achieve satisfactory sex attribution rates either based on biometrics or accurate plumage observation, possibly even from a distance.